The growing threat of antimicrobial resistance makes rapid and sensitive detection of bacterial pathogens in human samples an urgent need. In the case of blood infection, or bacteremia, standard pathogen...

The extraordinary capabilities of the biological sense of smell remain unmatched by electronic noses. Here, we present a revolutionary concept for next-generation electronic noses that integrates both specific and cross-reactive recognition principles within a single system. A novel biomimetic opto-electronic nose with enhanced performance based on Surface Plasmon Resonance Imaging (SPRI) was developed, combining cross-reactive peptides with selective Phage Display-derived peptides. Using Phage Display, five highly selective peptides were identified for detecting BTEX compounds (Benzene, Toluene, Ethylbenzene and Xylene). Experimental results demonstrate their high sensitivity and selectivity toward aromatic volatile organic compounds (VOCs), as well as the critical role of humidity in preserving peptide binding activity in the gas phase. The resulting biomimetic opto-electronic nose exhibits superior performance in the detection and discrimination of pure VOCs from various chemical families, as well as complex mixtures, including environmentally relevant pollutants. This proof-of-concept study establishes a foundation for the next generation of electronic noses, bridging biomimicry and optical sensing to achieve enhanced chemical recognition capabilities.

Detection and analysis of volatile organic compounds (VOCs) are crucial in diverse field. However, their rapid, sensitive and accurate detection by electronic nose (eN) remains a challenge. In this project, we report for the first time the use of protein amyloid fibrils as novel sensing material for VOC detection, combined with an eN approach based on surface plasmon resonance imaging (SPRI). Thanks to their unique structure, high surface area, and adaptable chemistry, short amyloid fibrils interact effectively with VOCs, and the obtained SPRI-based electronic nose allows real-time, label-free monitoring of these interactions. The results highlight the potential of protein-based nanostructures to bridge biology and technology in artificial olfaction.

Protein adsorption at interfaces is an important fundamental phenomenon that occurs in both natural and engineered systems. Despite recent advances in research on protein-interface adhesion, a lack of understanding persists regarding the interactions that occur on different surfaces and under various conditions, including pH, ionic strength, and temperature. Barnacle-inspired proteins are as promising biomolecules for investigating bioadhesive properties in wet conditions, since their natural adhesive mechanisms provide valuable insights into surface interactions. In this study, a recombinant protein called M19-2, inspired by the sequence of the barnacle protein Mrcp19, was produced in Escherichia coli and purified. The adsorption behavior of M19-2 on relevant self-assembled monolayer (SAM) surfaces with various physicochemical properties was studied using surface plasmon resonance imaging (SPRi). The present work investigated the effects of pH, temperature, and ionic strength on its binding characteristics. The results were then compared to those of model proteins, including human Fibrinogen, bovine serum albumin, and lysozyme. It was demonstrated that the M19-2 presented higher adsorption at an acidic pH compared to a neutral and basic pH, across various surfaces with different physicochemical properties. Moreover, temperature, ionic strength, pH, and protein concentration all affected the protein adsorption on different surfaces. Notably, the M19-2 exhibited stronger adsorption relative to its size compared to the selected model proteins. By addressing the existing gaps in the field of protein adsorption studies, this research provides valuable insights into protein-interface interactions, contributing significantly to the advancement of our understanding of bioinspired adhesive materials.

Over the past two decades, the use of odorant-binding proteins (OBPs) for the development of biosensors and bioelectronic noses (bioeNs) aimed at detecting and analyzing volatile organic compounds (VOCs) has been the subject of considerable research. However, there is a lack of fundamental studies for better understanding the interaction between OBPs and VOCs in gas phase. In this work, we investigated the effect of two key factors, namely relative humidity (RH) level and immobilization technique, on the selectivity of two OBP-based biosensors in gas phase. Concerning the effect of RH, the results showed that our active OBP (wild-type rat OBP3) lost its selectivity at 0% RH but retained good selectivity at 30% and 50% RH. To better understand the effect of this parameter, the hydration mechanism of the OBP was studied both experimentally and through molecular dynamics simulations. The effect of a cysteine residue, genetically added to the N-terminus of OBPs to control their orientation after immobilization on the chip, was evaluated. A significant reduction in selectivity was observed in the absence of cysteine. As expected, the introduction of this amino acid enabled to control the orientation of OBPs, making their binding pocket more accessible to VOCs and favoring specific interactions. Furthermore, we demonstrated that combining OBP-based biosensors with different properties can improve the discrimination capability of our bioeN. Finally, the ability of our system to detect essential oil vapors was tested, providing preliminary evidence that our bioeN is capable of detecting VOCs in complex media.

The early-stage diagnosis and monitoring of disease evolution is still one of the most challenging tasks in the field of cancer research. Several research have been driven toward the discovery of new cancer biomarkers as well as to the development of biosensors able to detect these biomarkers with high specificity and sensitivity. Many types of cancer have been detected at an advanced stage and, in particular, epithelial ovarian cancer (EOC) has a high incidence of diagnosis in the metastatic stage. This cancer is considered as the most aggressive type of gynecological cancer with a 5-year survival and until now, no specific biomarkers have been identified. Nevertheless, some studies have indicated that mesothelin, a protein overexpressed by tumour cells in the ovary, interacts with the CA-125 biomarker present in the blood system accelerating the metastatic process. Therefore, the simultaneous presence of CA-125 and mesothelin in the blood during the evolution of EOC could be used to diagnose this disease before the metastasis. Therefore, with this motivation, this work aimed at the development of a biosensor capable of simultaneously detecting mesothelin and CA-125 at low concentrations. A biosensor based on the surface plasmon resonance imaging (SPRi) technique was developed and gold nanoparticles (AuNPs) were used in order to enhance the sensitivity. The study analysed successive injections of the biomarkers CA-125 and mesothelin, both in solution (analytical range of 9–120 nM). The limits of detection were obtained for CA-125 and mesothelin, being of 3.03 nM and 13.62 nM, respectively. The biosensor detected mesothelin at a concentration close to the cutoff point for EOC (3 nM) and was able to detect the biomarker CA-125 at 9 nM. Furthermore, the biosensor interacted preferentially and simultaneously with the biomarkers CA-125 and mesothelin incubated in fetal bovine serum. Finally, the use of AuNPs increased the sensor signal for CA-125 detection compared to its direct detection and showed greater selectivity for both biomarkers. Therefore, the biosensor has important characteristics that allow testing with real samples. In a future project, it could be applied in the research of diagnosis and prognosis of EOC.

The cell-SELEX method enables efficient selection of aptamers that bind whole bacterial cells. However, after selection, it is difficult to determine their binding affinities using common screening methods because of the large size of the bacteria. Here we propose a simple surface plasmon resonance imaging method (SPRi) for aptamer characterization using bacterial membrane vesicles, called nanosomes, instead of whole cells. Nanosomes were obtained from membrane fragments after mechanical cell disruption in order to preserve the external surface epitopes of the bacterium used for their production. The study was conducted on Bacillus cereus (B. cereus), a Gram-positive bacterium commonly found in soil, rice, vegetables, and dairy products. Four aptamers and one negative control were initially grafted onto a biochip. The binding of B. cereus cells and nanosomes to immobilized aptamers was then compared. The use of nanosomes instead of cells provided a 30-fold amplification of the SPRi signal, thus allowing the selection of aptamers with higher affinities. Aptamer SP15 was found to be the most sensitive and selective for B. cereus ATCC14579 nanosomes. It was then truncated into three new sequences (SP15M, SP15S1, and SP15S2) to reduce its size while preserving the binding site. Fitting the results of the SPRi signal for B. cereus nanosomes showed a similar trend for SP15 and SP15M, and a slightly higher apparent association rate constant kon for SP15S2, which is the truncation with a high probability of a G-quadruplex structure. These observations were confirmed on nanosomes from B. cereus ATCC14579 grown in milk and from the clinical strain B. cereus J066. The developed method was validated using fluorescence microscopy on whole B. cereus cells and the SP15M aptamer labeled with a rhodamine. This study showed that nanosomes can successfully mimic the bacterial membrane with great potential for facilitating the screening of specific ligands for bacteria.

Foodborne pathogens present a serious issue around the world due to the remarkably high number of illnesses they cause every year. In an effort to narrow the gap between monitoring needs and currently implemented classical detection methodologies, the last decades have seen an increased development of highly accurate and reliable biosensors. Peptides as recognition biomolecules have been explored to develop biosensors that combine simple sample preparation and enhanced detection of bacterial pathogens in food. This review first focuses on the selection strategies for the design and screening of sensitive peptide bioreceptors, such as the isolation of natural antimicrobial peptides (AMPs) from living organisms, the screening of peptides by phage display and the use of in silico tools. Subsequently, an overview on the state-of-the-art techniques in the development of peptide-based biosensors for foodborne pathogen detection based on various transduction systems was given. Additionally, limitations in classical detection strategies have led to the development of innovative approaches for food monitoring, such as electronic noses, as promising alternatives. The use of peptide receptors in electronic noses is a growing field and the recent advances of such systems for foodborne pathogen detection are presented. All these biosensors and electronic noses are promising alternatives for the pathogen detection with high sensitivity, low cost and rapid response, and some of them are potential portable devices for on-site analyses.

Regardless of the promising use of nanoparticles (NPs) in biomedical applications, several toxic effects have increased the concerns about the safety of these nanomaterials. Although the pathways for NPs toxicity are diverse and dependent upon many parameters such as the nature of the nanoparticle and the biochemical environment, numerous studies have provided evidence that direct contact between NPs and biomolecules or cell membranes leads to cell inactivation or damage and may be a primary mechanism for cytotoxicity. In such a context, this work focused on developing a fast and accurate method to characterize the interaction between NPs, proteins and lipidic membranes by surface plasmon resonance imaging (SPRi) technique. The interaction of gold NPs with mimetic membranes was evaluated by monitoring the variation of reflectivity after several consecutive gold NPs injections on the lipidic membranes prepared on the SPRi biochip. The interaction on the membranes with varied lipidic composition was compared regarding the total surface concentration density of gold NPs adsorbed on them. Then, the interaction of gold and silver NPs with blood proteins was analyzed regarding their kinetic profile of the association/dissociation and dissociation constants (koff). The surface concentration density on the membrane composed of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine and cholesterol (POPC/cholesterol) was 2.5 times higher than the value found after the injections of gold NPs on POPC only or with dimethyldioctadecylammonium (POPC/DDAB). Regarding the proteins, gold NPs showed preferential binding to fibrinogen resulting in a value of the variation of reflectivity that was 8 times higher than the value found for the other proteins. Differently, silver NPs showed similar interaction on all the tested proteins but with a variation of reflectivity on immunoglobulin G (IgG) 2 times higher than the value found for the other tested proteins.

Silicon photonics can address a variety of applications, from datacom and biosensing to lidars. Recently, this technology has been explored for gas sensing. Detection and identification of odors remains a critical challenge in diverse areas such as air quality, food spoilage, or personal well-being. In this work, we present an olfactory sensor based on an array of 64 biofunctionalized Mach-Zehnder interferometers integrated on a silicon nitride platform. The ability to analyze odors at ppm level is demonstrated for several volatile organic compounds.

An electronic nose (e-nose) utilizes a multisensor array, which relies on the vector contrast of combinatorial responses, to effectively discriminate between volatile organic compounds (VOCs). In recent years, hierarchical structures made of nonbiological materials have been used to achieve the required sensor diversity. With the advent of self-assembling peptides, the ability to tune nanostructuration, surprisingly, has not been exploited for sensor array diversification. In this work, a designer surfactant-like peptide sequence, CG7-NH2, is used to fabricate morphologically and physicochemically heterogeneous "biohybrid" surfaces on Au-covered chips. These multistructural sensing surfaces, containing immobilized hierarchical nanostructures surrounded by self-assembled monolayers, are used for the detection and discrimination of VOCs. Through a simple and judicious design process, involving changes in pH and water content of peptide solutions, a five-element biohybrid sensor array coupled with a gas-phase surface plasmon resonance imaging system is shown to achieve sufficient discriminatory capabilities for four VOCs. Moreover, the limit of detection of the multiarray system is bench-marked at <1 and 6 ppbv for hexanoic acid and phenol (esophago-gastric biomarkers), respectively. Finally, the humidity effects are characterized, identifying the dissociation rate constant as a robust descriptor for classification, further exemplifying their efficacy as biomaterials in the field of artificial olfaction.

The last three decades have witnessed an increasing demand for novel analytical tools for the analysis of gases including odorants and volatile organic compounds (VOCs) in various domains. Traditional techniques such as gas chromatography coupled with mass spectrometry, although very efficient, present several drawbacks. Such a context has incited the research and industrial communities to work on the development of alternative technologies such as artificial olfaction systems, including gas sensors, olfactory biosensors and electronic noses (eNs). A wide variety of these systems have been designed using chemiresistive, electrochemical, acoustic or optical transducers. Among optical transduction systems, surface plasmon resonance (SPR) has been extensively studied thanks to its attractive features (high sensitivity, label free, real-time measurements). In this paper, we present an overview of the advances in the development of artificial olfaction systems with a focus on their development based on propagating SPR with different coupling configurations, including prism coupler, wave guide, and grating.

The sensitive, selective and real-time detection of odors, in the form of volatile organic compounds (VOCs), remains an important challenge in modern science. As a result, in the field of artificial olfaction, subsequent advances in sensor technologies have given rise to a variety of gas sensors spanning to address a large plethora of applications such as medical diagnostics, quality control, environmental monitoring and etc. Currently, however, the development of electronic nose (eN) technology has garnered the most attention with its biomimetic approach of multi-sensor systems. This study focuses on such an opto-eN system, which utilises Surface Plasmon Resonance Imaging (SPRI) as its transduction technique, operating in gas phase. The immediate requirement, therein, lies on the robustness of these system, especially in their ability to produce reliable measurement during in situ/on field applications. In this regard, temperature and humidity variations, regionally and seasonally, have shown to cause the most significant impact. Their influence on the signal is integrated, with chemical and physical contributions arising from both the immobilized sensing receptors and the metallized SPRI prism, responsible for the plasmonic behavior. Accordingly, we began by optimizing the prism metallization through a complete numerical study on metal layer configurations and thickness choices. The chosen structures were then experimentally compared for optimum performance and stability. Finally, the selected Chromium/Gold (Cr/Au) prism sample was used to test the effect of humidity and temperature. The developed numerical model was demonstrated to be a useful technique, which was experimentally coupled at various temperatures to obtain a fundamental understanding of the adsorption of water on gold surfaces. We believe that the comprehension of this phenomenon and its possible implications will be transferable and thereby useful for sensors beyond the opto-eN application.

The analysis of volatile organic compounds (VOCs) is an important issue in various domains. For this, electronic noses (eN) are very promising as novel analytical tools that are portable, inexpensive, and efficient for reliable and rapid analyses. Recently, we have demonstrated that surface plasmon resonance imaging (SPRI) is especially interesting for the development of eNs dedicated for gas-phase analysis of VOCs. To further improve the performance of the eN based on SPRI, in this study, we investigated the influence of the LED wavelength on the sensitivity of the system. For this, a complete theoretical study together with a related experimental investigation for the validation were carried out. We have shown that the wavelength of the light source has an impact on the surface sensitivity of SPRI for the detection of VOCs. Indeed, in the studied wavelength range from 530 nm to 740 nm, both bulk sensitivity and surface sensitivity increase as the wavelength increases with good coherence between theoretical and experimental results. With the optimal LED wavelength, the detection limits of our eN reach low ppb range for VOC such as 1-butanol.

Fast detection of bacteria in samples presumed to be un-contaminated, such as blood, is of great importance. Indeed, rapid diagnosis allows the set-up of appropriate antibiotic treatment. Besides clinical issues, there are many other domains, such as food processing or drug manufacturing, where the strict absence of any bacteria has to be assessed. Because the bacterial load found in most contaminated samples is often below the limit of detection for currently validated assays, a preliminary enrichment step is required to allow bacterial multiplication before proceeding to the analysis step, whatever it might be cultural, immunological or molecular methods. In this study, we describe the use of a biosensor for single-step bacteria detection. The whole analysis is performed in less than 20 h, during the growth phase of the micro-organisms, using an array of antimicrobial peptides (AMPs) coupled with a surface plasmon resonance imager (SPRI). A wide range of bacterial strains are assayed, showing differentiated affinity patterns with the immobilized peptides, which are confirmed by multivariate analysis. This work establishes the evidence that antimicrobial peptides, mostly used so far in the antibiotic drug industry, are suited for the wide-spectrum detection of unknown bacteria in samples, even at very low initial loads. Moreover, the small set of AMPs that were assayed provided a specific affinity profile for each pathogen, as confirmed by multivariate analyses. Furthermore, this work opens up the possibility of applying this method in more complex and relevant samples such as foodstuff, urine or blood.

Electronic Nose (eN) systems use sensor arrays containing multiple probes to generate fingerprints for the sensitive and selective detection of Volatile Organic Compounds (VOCs). In this paper, we analyzed the effect of VOC concentrations and of temperatures from 5°C to 35°C on the equilibrium response profiles. Fingerprint patterns for 1-butanol are strongly conserved thanks to a quadratic normalization of the row equilibrium data obtained from our opto-eN with Surface Plasmon Resonance imaging (SPRi) detection. Furthermore, a power law behavior of the rescaling factor with VOC concentration was observed and led to a Limit Of Detection (LOD) of 70 ppb for 1-butanol at 25°C.

Nowadays, the analysis of volatile organic compounds (VOCs) is very important in various domains. In the last decades, electronic noses have emerged as promising alternatives to traditional analytical methods. Nevertheless, their wide use is still limited by their performances such as low selectivity. Herein, we developed an optoelectronic nose using virtually screened peptides and hairpin DNA (hpDNA) with improved selectivity as sensing materials and surface plasmon resonance imaging (SPRi) as the detection system. Thanks to the complementarity of their binding properties towards target VOCs, the obtained optoelectronic nose has very good selectivity, being able to discriminate not only between VOCs of different chemical families, but also VOCs of the same family with only 1-carbon difference. The combination of these sensing materials with SPRi is relevant for the development of optoelectronic nose with large sensor arrays and improved performances.

Bloodstream bacterial infections are life-threatening conditions necessitating prompt medical care. Rapid pathogen identification is essential for early setting of the best anti-infectious therapy. However, the bacterial load in blood samples from patients with bacteremia is too low and under the limit of detection of most methods for direct identification of bacteria. Therefore, a preliminary step enabling the bacterial multiplication is required. To do so, blood cultures still remain the gold standard before bacteremia diagnosis. Bacterial identification is then usually obtained within 24 to 48 hours -at least- after blood sampling. In the present work, the fast and direct identification of bacteria present in blood cultures is completed in less than 12 hours, during bacterial growth, using an antibody microarray coupled to a Surface Plasmon Resonance imager (SPRi). Less than one bacterium (Salmonella enterica serovar Enteritidis) per milliliter of blood sample is successfully detected and identified in blood volumes similar to blood tests collected in clinics (i.e. several milliliters). This proof of concept demonstrates the workability of our method for human samples, despite the highly complex intrinsic nature of unprocessed blood. Our label-free method then opens new perspectives for direct and faster bacterial identification in a larger range of clinical samples.